G2TT
A Belief Network Approach to Optimization and Parameter Estimation in Resource and Environmental Management Models.
Varis O
发表日期1995
出版者IIASA, Laxenburg, Austria: WP-95-011
出版年1995
语种英语
摘要This study presents an approach to use Bayesian belief networks in various optimization tasks in resource and environmental management. A belief network is constructed to work parallel to a deterministic model, and it is used to update conditional probabilities associated with different components of the model. The propagation of probabilistic information occurs in two directions in the network. The divergence between prior and posterior probability distributions at model components can be used as indication on inconsistency between model structure, parameter values, and other information used. An iteration scheme was developed to force prior and posterior distributions to become equal. This removes inconsistencies between different sources of information. The scheme can be used in different optimization tasks including parameter estimation and optimization between various management alternatives. Also multiobjective optimization is possible. The approach is illustrated with two numerical examples and with a hypothetical example on cost-effective management of river water quality.
URLhttp://pure.iiasa.ac.at/id/eprint/4581/
来源智库International Institute for Applied Systems Analysis (Austria)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/124470
推荐引用方式
GB/T 7714
Varis O. A Belief Network Approach to Optimization and Parameter Estimation in Resource and Environmental Management Models.. 1995.
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